Study on Learner Model in Adaptive Learning System Based on Ant Colony Algorithm

Abstract

The adaptive learning system is a hotspot in the field of e-Learning and intelligent education researches. Learner model is the core of adaptive learning system. However, in the light of rapidly growing “big data”, adaptive learning system is facing the challenge of dealing with the realistic data. So in order to respond to this situation, we take a summary of oversea and domestic learner model norm of e-Learning, and then explore the ant colony algorithm and propose a construction method of learner model with consideration on the learners’ knowledge, interests and individual traits in the adaptive learning system. Especially, we regard the learners’ cognitive ability as a vital aspect of the learner model, and creatively employ the forgetting curve to the quantitative learner model built on ant colony algorithm.